matlab_小波去噪,实现阈值小波去噪，含有frost去噪，并且输出信噪比

tic; i=imread('lena1.jpg'); subplot(2,3,1);imshow(i); title('原图像');%axis on; %生成含噪图像并显示 j=imnoise(i,'gaussian',0,0.01); %g=imnoise(f,'gaussian',m,var)将均值M,方差为var的高斯噪声加到图像f上，默认值为均值是0，方差是0.01的噪声。 subplot(2,3,4);imshow(j);title('含噪图像');%axis on; %计算含噪图像PSNR值 PSNR1= psnr( j,i ); %{ %进行去噪 %[Ba,thresh]=BayesThresh2(j); So = SoftThresh(j,0.0134); subplot(2,3,2);imshow(So); title('软阈值去噪后图像');%axis on; %计算软阈值去噪图像PSNR值 PSNR2= psnr( So,i ); Ha = HardThresh(j,0.0134); subplot(2,3,5);imshow(Ha); title('硬阈值去噪后图像');%axis on; %计算硬阈值去噪图像PSNR值 PSNR3= psnr( Ha,i ); %} ft = frost(j); subplot(2,3,2);imshow(ft); title('frost去噪后图像');%axis on; %计算frost去噪图像PSNR值 PSNR2= psnr( ft,i ); ft_Wa = wavelet( ft,i); subplot(2,3,3);imshow(ft_Wa); title('frost+小波去噪后图像');%axis on; %计算小波阈值去噪图像PSNR值 PSNR3= psnr( ft_Wa,i ); Wa = wavelet( j,i); subplot(2,3,5);imshow(Wa); title('小波去噪后图像');%axis on; %计算小波阈值去噪图像PSNR值 PSNR4= psnr( Wa,i ); Wa_ft = frost(Wa); subplot(2,3,6);imshow(Wa_ft); title('小波+frost去噪后图像');%axis on; %计算小波阈值去噪图像PSNR值 PSNR5= psnr( Wa_ft,i ); toc;